Field
Aspects of the present inventions relate to “Sales Force Automation” or “Sales Force Management” systems (hereinafter collectively referred to as “SFA”) and other systems that rely on data entry by users, data quality enforcement and facilitation for those systems, and both Big Data Analytics and Business Analytics, and, more particularly, to systems and methods for providing user-centric tools that help companies to facilitate and enforce both user software adoption and data quality in user data entries; automate data collection tasks and distill large volumes of relevant data from telecom networks and devices, data networks and devices, billing systems, mobile and other computing and communications devices; shorten the time needed to make that data useful and available; provide real-time access to data while making that data more user-centric and consumable by business stakeholders; and translate large volumes of transactional data into business insight to drive business decision-making.
Aspects of the present inventions utilize a data-driven approach to solving the core data quality issues for systems that collect information from users via data entry, such as Customer relationship Management and Sales Force Automation systems, and enhances those systems with actionable insight derived from objective data sources and the data quality facilitation and enforcement mechanisms described herein.
Description of Related Information
Too much data is a massive analysis issue. The volume, variety and velocity of newly available data sources challenge IT leaders to extract actionable insight from those sources while the veracity of related user data entries often complicates those challenges. As such, some of the solutions/innovations herein are designed to make sense of Big Data and other data sources to find patterns that help organizations better manage their data quality and employees, and gain new insights that enable them to make better financial projections and better manage their sales processes.
Further, drawbacks of current “Sales Force Automation” or “Sales Force Management” systems (hereinafter referred to as “SFA” and/or “SFM”) include or involve aspects of failing to effectively address one or more of 3 core issues adoption, data integrity and/or productivity. For example, many such systems suffer with respect to adoption in being unable to address issues of salespeople failing to enter relevant data into the system on a timely basis or at all. Further, many suffer drawbacks with respect to data integrity, such as issues relating to sales pipeline projections that are often overly optimistic. Finally, such systems have drawbacks with respect to accurate productivity measures, such as when level(s) of productive activity may not bode well for future sales results in future quarters, but management may not have a reliability check on the level of sales prospecting and sales process activity that may be lacking.
In sum, there is a need for systems and methods that may adequately address these and other drawbacks.